We are looking for talented Senior Product Analysts ready to join our growing team. In this role, you will support the game teams within, working alongside other analysts and data scientists . You will encounter a variety of challenges covering the full data work spectrum, from data mining to reporting, and have an opportunity to support different business stakeholders. Your contribution will help shape Product Madness games into their best versions yet
What You'll Do
The aim of this role is to ensure the game teams are making informed decisions based on actionable insights and recommendations. Therefore your key responsibilities will include:
Working closely with the game team in supporting their day-to-day data needs
Providing insights necessary to optimise existing and build new in-game features
Sharing your findings with the game teams and the wider Product Madness community
Creating reports to help with capturing all of our daily KPIs in areas such as player engagement or monetisation
Monitoring the ever changing in-game behaviour of players exposed to GameOps events and AB Tests
Investigating arising in-game issues and data anomalies
Implementing in-game tracking and producing end to end data pipelines that empower end users alongside the data engineering team
Uncovering new perspectives that help us continue to delight the people playing our games.
Championing creativity in the way we we think, design, test, verify and implement new solutions
To do this successfully we believe you are:
Passionate about quantitative analysis
Intuitive and proactive with regards to data interpretation
Capable to generate actionable business insights for the game teams and Product Madness as a whole
Experienced in working with game or similar user experience focused datasets
Excited to work closely with a diverse team of business stakeholders, product analysts and data scientists
What We're Looking For
4+ years experience in a product or data analyst role
1+ year of experience from working with other F2P games, social casino titles or RMG or general knowledge about the mobile games industry or similarly sophisticated customer-facing digital businesses
Strong SQL and Excel skills
Experience in data visualization and reporting tools such as Looker/QlikView/Tableau/etc.
Working experience setting up and analyzing A/B-tests
Experience in handling complex problems and communicate the solutions to varied audiences
Ability to translate game needs into data analytics requirements
Strong in mathematics and quantitative analysis with a passion for numbers and data
Why Product Madness?
You will be joining a global powerhouse where you will be part of a world-class talented team that creates remarkable hit games such as Heart of Vegas, Lightning Link, Cashman Casino, Mighty Fu, and Big Fish Casino. The success of these titles has led to over 400 million downloads and more than 50 million active users. But there is no stopping us there, we also have a new games team that is working on bringing new hit games to the market. Product Madness is an Aristocrat Technologies company within its digital games division of Pixel United.
Outstanding growth has seen us build Product Madness to more than 800 team members and counting, you can join one of our seven global talent hubs including London, USA, Canada, Spain, Poland, Ukraine & Israel.
You will be part of a company that is not only Mad about games but Mad about our people. Living by our value of people first, you will feel this firsthand from the moment you step into one of our fantastic studios. This is made possible by our amazing studio experience team who help make Product Madness such a fun place to work. Be it arranging endless snacks, weekly breakfasts & lunches, lavish Christmas & summer parties, happy hour drinks, social get-togethers and so much more.
So what is stopping you from coming and joining the Madness?
Travel Expectations
Pay Range
$119,765 - $222,422 per year
Our goal is to pay a market competitive salary focusing near the median of our pay ranges. However, final offers for all positions will be based on several factors such as experience level, education, skills, work location, and internal pay equity.
